(navigation image)
Home American Libraries | Canadian Libraries | Universal Library | Community Texts | Project Gutenberg | Children's Library | Biodiversity Heritage Library | Additional Collections
Search: Advanced Search
Anonymous User (login or join us)
Upload
See other formats

Full text of "Rapid Population Growth Consequences And Policy Implications"

140                                                                      RAPID POPULATION GROWTH-II
tenuous.* The interrelationship of urbanization and natality is also less stable than other indices shown. When the most urban countries, Argentina and Uruguay, are removed, and the correlation is confined to the remaining twenty-three countries of the region, the correlation coefficient drops from -0.75 to -0.60.t These findings confirm the conclusions, reached by a number of investigators, that in Latin America natality is not so closely linked with industrialization and urbanization as it was historically in Europe. Other aspects of development appear to be more closely related to birth rates in Latin America.
The relationships between socioeconomic indices and natality may take different forms. In Table 4 it will be observed that a curvilinear regression (single asymptotic curve) fits the data somewhat better and explains more of the variance than linear regressions. This is especially true of literacy.
Logically, natality rates should be lagged behind their presumed socio-economic determinants; but it is not clear what amount of lag is appropriate or that this is a constant among different socioeconomic variables. Further exploration of this subject is required.
On the basis of empirical experience in Latin America, threshold ranges were determined for each of the variables used. This was done by contrasting the indicators for the seven countries of the region that had entered or gone through the transition with those of the eighteen that had not.$
The threshold range for each socioeconomic indicator is shown in Table 5. This range was much too great for the measure of urbanization (percent of
*The seven socioeconomic variables shown in Table 4 were selected from a very much larger number which produced lower but often statistically significant zero order correlations with crude birth rates. The seven variables selected arc not only highly correlated with birth rates but also with each other, such intercorrelations ranging in magnitude from 0.64 to 0.94, with an average of 0.78. All the intercorrela tions are statistically significant, half of them at the 0.1 percent level.
Correlations between specific economic measures and crude birth rate were: average annual rate of growth of real domestic product, 1960-65 (0.35); per capita gross domestic product, 1963 (-0.42); per capita national income, 1963 (-0.49); gross domestic fixed capital formation as percent of gross domestic product at 1962 market prices (-0.43); percent of income originating in the agricultural (0.47) and manufacturing (-0.21) sectors to the gross domestic product at factor cost, 1962; energy consumption per capita, 1962 (-0.26); percent of economically active males in agriculture (0.85) and in industry (-0.60).
tin a sample of only twenty-five countries and with data of greatly varying quality, single figures should not be taken very seriously. Thus the extraordinarily high correlation of telephones (i.e., a surrogate for modern infrastructure) with natality is reduced from -0.94 to -0.88 when Argentina and Uruguay arc excluded.
tThc seven countries are Argentina, Barbados, Chile, Cuba, Puerto Rico, Trinidad and Tobago, and Uruguay. The threshold was determined by the range between the lowest value for the first group of countries and the highest for the second. To take a specific example: the lowest figure reported for female expectation of life at birth (e0) in the first group was 59 in Chile; the highest in the second group of countries was 67 in